1. Field of the Invention
The present invention relates to a speech recognition system, and more particularly relates to a speech recognition system that is insensitive to external noise, carries out an efficient calculation, and is applicable to actual life thereby.
2. Description of the Related Art
Recently, as the technique of speech recognition field is developed, the usage of speech recognition is diversified.
FIG. 1 is a block diagram roughly illustrating the structure of a prior speech recognition system.
As described in FIG. 1, a speech recognition system mainly comprises a characteristic extraction section (2) and a recognizer (4). In other words, a prior characteristic extraction method such as a linear prediction coding analysis (LPC) has been used for an input voice signal characteristic extraction, and a hidden Markov Model (HMM) receiver has been widely used.
In addition, as a speech recognition system applicable to real electronic products, a speech recognition system using an auditory model and a neural network has been developed. One of the prior speech recognition systems having the features described above is disclosed in Korean patent No. 180651 registered on Dec. 2, 1998.
Looking into the patented invention mentioned above, it comprises an A/D converter that converts analog voice signals to digital signals, a filtering section that filters the 12-bit digital signals converted at the A/D converter into prescribed numbers of channels, a characteristic extraction section that extracts voice characteristics having strong noise-resistance from the output signals of the filtering section and outputs the extraction result, a word boundary detection section that discriminates the information of the start-point and the end-point of the voice signal on the basis of the voice signal converted into the digital signal, and an analysis/transaction section that codes and outputs the final result by carrying out a timing normalization and a classifying process using a neural network on the basis of the voice characteristics provided by the characteristic extraction section and the information of the start-point and the end-point of voice signal from the word boundary detection section.
However, since the prior speech recognition system described above employs LPC method or the like as a characteristic extraction method and HMM as a recognizer, it has difficulties in embodying an ASIC. And it is therefore difficult to be applied to actual life because it has to handle software only or construct a complex system using DSP.
Besides, the prior art has more problems that the power consumption is large because digital signals converted at A/D converter are filtered at filtering section into numbers of channels, and the efficiency is low because it detects the word boundary first and extracts voice characteristics thereafter.